Building an Intelligent Recommendation System with Neo4j, Spring AI, and LangChain4j
In this third part of the book, we’ll look at building a recommendation application using the Spring AI and LangChain4j frameworks. We will look at leveraging LLMs and GraphRAG to enhance the graph to lay the foundation for building better recommendation applications. We will further enhance the graph by leveraging Graph Data Science algorithms such as KNN similarity and community detection to augment the graph to deliver better recommendations. We will also take a look at how using these algorithms is the better approach over basic vector search. This part of the book includes the following chapters:
This part of the book includes the following chapters:
- Chapter 7, Introducing the Neo4j Spring AI and LangChain4j Frameworks for Building Recommendation Systems
- Chapter 8, Constructing a Recommendation Graph with the H&M Personalization Dataset
- Chapter 9, Integrating...
